Abstract
A new method for improving the accuracy of gridded sea surface salinity (SSS) fields is proposed in this paper. The method mainly focuses on dual quality–distance weighting of the Aquarius level 2 along-track SSS data according to quality flags, which represent nonnominal data conditions for measurements. In the weighting progress, 14 data conditions were considered, and their geospatial distributions and influences on the SSS were also visualized and evaluated. Three interpolation methods were employed, and weekly gridded SSS maps were produced for the period from September 2011 to May 2015. These maps were evaluated via comparisons with concurrent Argo buoy measurements. The results show that the proposed method improved the accuracy of the SSS fields by approximately 36% compared to the officially released weekly level 3 products and yielded root mean squared difference (RMSD), correlation and bias values of 0.19 psu, 0.98 and 0.01 psu, respectively. These findings indicate a significant improvement in the accuracy of the SSS fields and provide a better understanding of the influences of different conditions on salinity.
Highlights
Sea surface salinity (SSS) is one of the most important parameters in marine dynamics and is closely related to large-scale ocean circulation and climate change [1,2]
The results show that the accuracy of the output of our Weighted average fitting (WAF) method is improved by approximately 36% compared to the officially released weekly level 3 (L3) products
The key aspect of the method is the dual weighting of the data according to quality flags
Summary
Sea surface salinity (SSS) is one of the most important parameters in marine dynamics and is closely related to large-scale ocean circulation and climate change [1,2]. SSS values can be effectively measured based on data from the Aquarius satellite. Electromagnetic radiation emissions from the sea surface can be measured in the form of equivalent brightness temperatures in Kelvin by the Aquarius satellite and converted into SSS after applying corrections for various geophysical effects. The officially released standard Aquarius gridded SSS level 3 (L3) data products are generated from level 2 (L2) salinity data without any additional adjustments for climatology, reference model output or in situ data [5]. Official Aquarius version 5.0 products have been published, and the accuracy of the monthly L3 1◦ SSS fields has been estimated via a triple point analysis using individual matchups among Aquarius data, Argo float data and Hybrid Coordinate Ocean Model (HYCOM) data [10,11]. The triple point analysis results showed that the monthly average RMSD of the Aquarius L3 field data was 0.128 psu, whereas the mean RMSD between the weekly
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